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Generative AI in Ship Design by Thakur, Sahil; Saxena, Navneet V; Roy, Prof Sitikantha is a scholarly article available to read on EtoBox.

What is Generative AI in Ship Design about?

The process of ship design is intricate, heavily influenced by the hull form which accounts for approximately 70% of the total cost. Traditional methods rely on human-driven iterative processes based on naval architecture principles and engineering analysis. In contrast, generative AI presents a novel approach, utilizing computational algorithms rooted in machine learning and artificial intelligence to optimize ship hull design. This report outlines the systematic creation of a generative AI for this purpose, involving steps such as dataset collection, model architecture selection, training, and validation. Utilizing the "SHIP-D" dataset, consisting of 30,000 hull forms, the report adopts the Gaussian Mixture Model (GMM) as the generative model architecture. GMMs offer a statistical framework to analyze data distribution, crucial for generating innovative ship designs efficiently. Overall, this approach holds promise in revolutionizing ship design by exploring a broader design space and integrating multidisciplinary optimization objectives effectively.

Author

Thakur, Sahil; Saxena, Navneet V; Roy, Prof Sitikantha

Published

2024

Language

EN